Research on K Anonymity Algorithm based on Association Analysis of Data Utility
More and more medical data are shared,which leads to disclosure of personal privacy information.Therefore,the construction of medical data privacy preserving publishing model is of great value: not only to make a non-correspondence between the released information and personal identity,but also to maintain the data utility after anonymity.However,there is an inherent contradiction between the anonymity and the data utility.In this paper,a Principal Component Analysis-Grey Relational Analysis(PCA-GRA)K anonymous algorithm is proposed to improve the data utility effectively under the premise of anonymity,in which the association between quasi-identifiers and the sensitive information is reckoned as a criterion to control the generalization hierarchy.Compared with the previous anonymity algorithms,results show that the proposed PCA-GRA K anonymous algorithm has achieved significant improvement in data utility from three aspects,namely information loss,feature maintenance and classification evaluation performance.
Privacy preserve K anonymity data utility association analysis
Yuanxiunan Gao Tao Luo Jianfeng Li Cong Wang
Beijing Key Laboratory of Network System Architecture and Convergence,Beijing University of Posts an Software College,Beijing University of Posts and Telecommunications Beijing,China
国际会议
重庆
英文
426-432
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）